CN117910493A - Drug label identification method, device, computer equipment and storage medium - Google Patents

Drug label identification method, device, computer equipment and storage medium Download PDF

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Publication number
CN117910493A
CN117910493A CN202311664088.2A CN202311664088A CN117910493A CN 117910493 A CN117910493 A CN 117910493A CN 202311664088 A CN202311664088 A CN 202311664088A CN 117910493 A CN117910493 A CN 117910493A
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medicine
information
drug
target
medication
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夏敏
王胜
许辉
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Anhui Provincial Hospital First Affiliated Hospital Of Ustc
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Anhui Provincial Hospital First Affiliated Hospital Of Ustc
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06K—GRAPHICAL DATA READING; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K17/00—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations
    • G06K17/0022—Methods or arrangements for effecting co-operative working between equipments covered by two or more of main groups G06K1/00 - G06K15/00, e.g. automatic card files incorporating conveying and reading operations arrangements or provisions for transferring data to distant stations, e.g. from a sensing device
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

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  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medicinal Chemistry (AREA)
  • Epidemiology (AREA)
  • Chemical & Material Sciences (AREA)
  • Medical Informatics (AREA)
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  • General Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

The application relates to the technical field of medicine identification, and provides a medicine label identification method, a device, equipment and a medium. And when the first medicine information and the second medicine information are consistent, regenerating the corresponding medicine label. Therefore, multi-terminal identification and verification of medicine information can be realized, and the identification accuracy of the intelligent medicine car to the medicine label is improved.

Description

Drug label identification method, device, computer equipment and storage medium
Technical Field
The present application relates to the field of medicine identification technologies, and in particular, to a method and apparatus for identifying a medicine label, a computer device, and a storage medium.
Background
The intelligent medicine car is used for realizing intelligent management functions such as intelligent storage, distribution, counting, automatic identification and the like of medicines. The intelligent medicine car can accurately identify and record the medicine quantity through the weighing technology, and meanwhile, the type and the dosage of medicines can be identified through the medicine scanning equipment.
When the intelligent medicine cart dispenses, information such as the types and the quantity of medicines can be printed through the label printing equipment. At present, the identification of label information of the intelligent medicine cart to the medicine is realized according to the label information on the medicine bottle and the weighing information of the medicine. However, this method has a risk of incorrect identification, for example, when a foreign object exists on the weighing table, the weighing result is affected, and the medicine does not conform to the label information on the medicine bottle, so that the identification accuracy of the medicine label is low.
Therefore, how to improve the identification accuracy of the drug label of the intelligent drug cart is a technical problem to be solved.
Disclosure of Invention
The application provides a drug label identification method, a device, computer equipment and a storage medium, aiming at improving the drug label identification accuracy of an intelligent drug vehicle.
In a first aspect, the present application provides a method of identifying a drug label, the method comprising:
acquiring a medicine bottle image and medicine bottle weight information of a target medicine bottle and a medicine image and medicine weight information of a target medicine;
Identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and the medicine bottle weight information;
determining second medicine information of the target medicine based on the medicine image and the medicine weight information;
and when the first medicine information is consistent with the second medicine information, generating a medicine label of the target medicine based on the first medicine information and/or the second medicine information.
Further, the determining second medicine information of the target medicine based on the medicine image and the medicine weight information includes:
Identifying the number of the target medicines and appearance information of the target medicines based on the medicine images;
determining a single product weight of the target drug based on the number of target drugs and the drug weight information;
And based on the appearance information of the target medicine and the weight of the single product, comparing and inquiring in a preset medicine information base to obtain the second medicine information.
Further, the appearance information of the target medicine includes an appearance type, a shape, and a color of the target medicine.
Further, the comparing and inquiring in a preset medicine information base based on the appearance information of the target medicine and the weight of the single product, before obtaining the second medicine information, further includes:
Acquiring data in the field of medicine profession;
extracting professional medicine information in the medicine professional field data based on a preset medicine information category;
And constructing the medicine information base based on the professional medicine information.
Further, after determining the second medicine information of the target medicine based on the medicine image and the medicine weight information, the method further includes:
And when the first medicine information is inconsistent with the second medicine information, generating error reminding information so as to remind a user of dispensing errors.
Further, when the first medicine information is inconsistent with the second medicine information, generating error reminding information to remind a user of dispensing errors, including:
extracting difference information of the first medicine information and the second medicine information when the first medicine information is inconsistent with the second medicine information;
Determining an error category of the dispensing error based on the difference information;
And determining the error reminding information corresponding to the error category based on a preset error information list and the error category, and generating the error reminding information.
Further, the first medicine information and the second medicine information include a medicine kind, a medicine name, and a medicine number.
In a second aspect, the present application also provides a drug label identification device comprising:
The medicine information acquisition module is used for acquiring medicine bottle images and medicine bottle weight information of the target medicine bottle and medicine images and medicine weight information of the target medicine;
A first medicine information identification module for identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and medicine bottle weight information;
a second medicine information identification module for determining second medicine information of the target medicine based on the medicine image and the medicine weight information;
And the drug label generating module is used for generating a drug label of the target drug based on the first drug information and/or the second drug information when the first drug information is consistent with the second drug information.
In a third aspect, the present application also provides a computer device comprising a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program when executed by the processor implements the steps of the drug label identification method as described above.
In a fourth aspect, the present application also provides a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of a drug label identification method as described above.
The application provides a medicine label identification method, a device, equipment and a storage medium, wherein the method comprises the steps of acquiring medicine bottle images and medicine bottle weight information of a target medicine bottle and medicine images and medicine weight information of a target medicine; identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and the medicine bottle weight information; determining second medicine information of the target medicine based on the medicine image and the medicine weight information; and when the first medicine information is consistent with the second medicine information, generating a medicine label of the target medicine based on the first medicine information and/or the second medicine information. By the method, the first medicine information of the medicine corresponding to the target medicine bottle is identified by collecting the medicine bottle image and the medicine bottle weight of the target medicine bottle, and the second medicine information of the target medicine is identified by collecting the medicine image and the medicine weight information of the target medicine, so that the identification result of the medicine label is judged according to the comparison result of the first medicine information and the second medicine information. And when the first medicine information and the second medicine information are consistent, regenerating the corresponding medicine label. Therefore, multi-terminal identification and verification of medicine information can be realized, and the identification accuracy of the intelligent medicine car to the medicine label is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a first embodiment of a drug label identification method provided by the application;
FIG. 2 is a flowchart of a second embodiment of a drug label identification method provided by the present application;
FIG. 3 is a flowchart illustrating a third embodiment of a drug label identification method according to the present application;
fig. 4 is a schematic structural view of a first embodiment of a drug label identification device provided by the present application;
fig. 5 is a schematic block diagram of a computer device according to an embodiment of the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, fig. 1 is a flowchart of a first embodiment of a drug label identification method according to the present application.
As shown in fig. 1, the drug label identification method includes steps S101 to S104.
Step S101, acquiring a medicine bottle image and medicine bottle weight information of a target medicine bottle and a medicine image and medicine weight information of a target medicine;
in one embodiment, the image acquisition device acquires the medicine bottle image of the target medicine bottle and the medicine image of the target medicine, and the weighing technology acquires the medicine bottle weight information of the target medicine bottle and the medicine weight information of the target medicine.
In one embodiment, weighing of the vials and medicines may be performed by a load cell (e.g., a pressure sensor).
In one embodiment, the medicine bottle label on the target medicine bottle can be collected through the multi-eye image sensor, then the collected medicine bottle label is restored through the image processing technology, and then the medicine information on the medicine bottle label is identified through the text identification technology.
In some scenarios, the captured image may not be clear enough, resulting in the inability to obtain tag information normally. Therefore, in the embodiment of the present application, the image processing technology may be an image recognition model trained by a neural network model (such as an AI Clear model), where the image recognition model further includes: and the high-definition image reconstruction module predicts high-frequency details in the image by analyzing the information in the image, and restores the high-frequency information of the image by the low-frequency information of the image, so that the image becomes clearer.
In one embodiment, the complete image of the drug vial label can also be acquired by a monocular image sensor in combination with a stepper motor to facilitate identification of drug information on the drug vial label.
In an embodiment, the image sensor is used for acquiring medicine information, the micro vibration platform can be matched, medicines are horizontally spread on the micro vibration platform through vibration, the phenomenon that the medicine stack causes unclear image acquisition is avoided, and the accuracy of image identification is improved.
Step S102, identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and the medicine bottle weight information;
In an embodiment, information of the current medicine type, number, etc. of the target medicine bottle may be identified as the first medicine information based on the label information and the medicine bottle weight information on the medicine bottle image.
Typically, the vials are labeled, and the information on the label includes information about the name of the drug, which patients are to be treated, etc. Therefore, after the medicine bottle image is acquired, the label information can be obtained. In order to accurately obtain the medicine bottle image, whether an image sensor or a camera is used, a plurality of medicine bottle images can be photographed from different angles.
Step S103, determining second medicine information of the target medicine based on the medicine image and the medicine weight information;
in one embodiment, information such as the appearance, type, number, and weight of the drug of the target drug may be identified based on the drug image and drug weight information.
In an embodiment, the first medicine information and the second medicine information include a medicine type, a medicine name, and a medicine number.
In an embodiment, by identifying the medicine bottle image, the medicine image and the corresponding weight information, information such as medicine name, kind and number of the medicine corresponding to the medicine bottle can be identified, and appearance information and weight information of the target medicine can be identified, so that information such as medicine name, kind and the like of the target medicine can be queried according to the appearance information.
Step S104, when the first medicine information is consistent with the second medicine information, generating a medicine label of the target medicine based on the first medicine information and/or the second medicine information.
In an embodiment, the first medicine information and the second medicine information are compared, and the first medicine information and the second medicine information are mutually verified, so that whether the medicine identification result is accurate or not is judged.
In an embodiment, when the first medicine information and the second medicine information are consistent, the medicine information corresponding to the medicine bottle and the medicine information corresponding to the target medicine are the same, and belong to the same medicine, at this time, the first medicine information and the second medicine information can be combined, so that corresponding medicine labels are generated, medicine dispensing and packaging are performed, and the medicine labels are printed and attached to the medicine bottles.
In one embodiment, the medication label may include information such as the name, number, type, usage, symptoms and medication notes.
The embodiment provides a medicine tag identification method, which is used for identifying first medicine information of a medicine corresponding to a target medicine bottle by collecting medicine bottle images and medicine bottle weights of the target medicine bottle and identifying second medicine information of the target medicine by collecting medicine images and medicine weight information of the target medicine, so that the identification result of the medicine tag is judged according to comparison results of the first medicine information and the second medicine information. And when the first medicine information and the second medicine information are consistent, regenerating the corresponding medicine label. Therefore, multi-terminal identification and verification of medicine information can be realized, and the identification accuracy of the intelligent medicine car to the medicine label is improved.
Referring to fig. 2, fig. 2 is a flowchart of a second embodiment of a drug label identification method according to the present application.
As shown in fig. 2, based on the embodiment shown in fig. 1, in this embodiment, the step S103 specifically includes:
step S201, based on the medicine image, identifying the quantity of the target medicines and the appearance information of the target medicines;
In one embodiment, after the drug image is acquired by the image sensor, the number of drugs in the drug image and the appearance information can be identified by the image processing technique.
In an embodiment, the appearance information of the target drug includes an appearance type, shape, and color of the target drug.
In one embodiment, the appearance type of the target drug may include a capsule type, a granule type, or the like.
In an embodiment, the appearance of the target drug may also include the shape of the drug, such as a circle, oval, etc., and may also include the size of the drug, etc.
In an embodiment, the color of the medicine is also an important reference basis for identifying the kind of medicine, and the color of the target medicine can be acquired through a color image sensor and further reduced through an image processing technology.
Step S202, determining the single product weight of the target medicine based on the quantity of the target medicine and the medicine weight information;
In one embodiment, the production of the medicines has strict production standards, and the weight of each medicine is within a certain weight range with very small error. The weights of the same medicine particles are basically the same, but the weights of different medicine particles may be different, so that the weight of a single target medicine particle can be calculated according to the result of dividing the total weight of the target medicine and the number of the target medicine, thereby being used as the basis of medicine identification.
And step 203, based on the appearance information of the target medicine and the weight of the single product, comparing and inquiring in a preset medicine information base to obtain the second medicine information.
In an embodiment, according to the appearance information of the target medicine and the weight of the single product, the target medicine can be quickly locked by comparing the medicine information base, so that the medicine information of the target medicine can be obtained. For example, if the target medicine is granular, the granular medicine can be directly inquired, and then the granular medicine is gradually screened according to the shape, the size, the weight, the color and the like.
Further, before the step S203, the method specifically further includes: acquiring data in the field of medicine profession; extracting professional medicine information in the medicine professional field data based on a preset medicine information category; and constructing the medicine information base based on the professional medicine information.
In an embodiment, the medicine information may be extracted according to the professional domain knowledge related to medicines in the pharmaceutical industry, and the medicine information category may be set according to the actual requirement, such as information of medicine name, characteristics, applicable symptoms, applicable crowd, components, medicine type, shape, weight, size, color, medicine information, medication notice, and the like. Then, the extracted medicine information is classified, and a medicine information base is constructed.
In one embodiment, the medicine information base can be classified according to the type of the medicinal medicines, such as infusion type, oral type and external type; the medicine can also be classified according to the appearance of the medicine, such as granules, capsules, liquids, gels and the like; classification can also be based on the field of administration, such as cardiac surgery, neurology, etc.
Referring to fig. 3, fig. 3 is a flowchart illustrating a third embodiment of a drug label identification method according to the present application.
As shown in fig. 3, based on the embodiment shown in fig. 1, in this embodiment, after step S103, the method specifically further includes:
Step S105, when the first medicine information is inconsistent with the second medicine information, generating error reminding information to remind the user of dispensing errors.
In an embodiment, when the first medicine information and the second medicine information are different and conflict, error reminding information is generated to remind a dispensing person (such as a doctor or a nurse) of the current dispensing error, so that the dispensing person can manually adjust in time, and the accuracy of medicine dispensing is guaranteed.
Further, when the first medicine information is inconsistent with the second medicine information, extracting difference information of the first medicine information and the second medicine information; determining an error category of the dispensing error based on the difference information; and determining the error reminding information corresponding to the error category based on a preset error information list and the error category, and generating the error reminding information.
In an embodiment, when the first medicine information and the second medicine information are inconsistent, if there is information that is not present in the other medicine information in one medicine information, the extraction may not be needed, for example, the first medicine information includes a medicine administration method, the second medicine information does not include the medicine administration method, and if there is no other medicine information that is consistent, the error reporting is not needed, and the two medicine information may be combined to generate the corresponding medicine label.
In an embodiment, when the first medicine information and the second medicine information are inconsistent and inconsistent information has conflict, for example, when the medicine quantity or the medicine weight is inconsistent, an error prompt can be generated, and error prompt information corresponding to an error category, for example, "medicine weight abnormality" corresponding to a weight difference category, "medicine quantity abnormality" corresponding to a medicine quantity difference category, and the like, are generated according to a preset error information list.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a first embodiment of a drug label identifying apparatus according to the present application, where the drug label identifying apparatus is used for executing the aforementioned drug label identifying method. Wherein, this medicine label recognition device can be disposed in the server.
As shown in fig. 4, the drug label recognition device 300 includes: a drug information acquisition module 301, a first drug information identification module 302, a second drug information identification module 303, and a drug label generation module 304.
A medicine information acquisition module 301, configured to acquire a medicine bottle image and medicine bottle weight information of a target medicine bottle, and a medicine image and medicine weight information of a target medicine;
A first medicine information identification module 302 for identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and medicine bottle weight information;
a second medicine information identification module 303 for determining second medicine information of the target medicine based on the medicine image and the medicine weight information;
And a drug label generating module 304, configured to generate a drug label of the target drug based on the first drug information and/or the second drug information when the first drug information is consistent with the second drug information.
In an embodiment, the second medicine information identifying module 303 is further configured to identify the number of the target medicines and appearance information of the target medicines based on the medicine image; determining a single product weight of the target drug based on the number of target drugs and the drug weight information; and based on the appearance information of the target medicine and the weight of the single product, comparing and inquiring in a preset medicine information base to obtain the second medicine information.
In an embodiment, the appearance information of the target drug includes an appearance type, shape, and color of the target drug.
In an embodiment, the drug label identifying apparatus 300 further includes a drug information base construction module for acquiring data of the pharmaceutical professional field; extracting professional medicine information in the medicine professional field data based on a preset medicine information category; and constructing the medicine information base based on the professional medicine information.
In an embodiment, the drug label identifying apparatus 300 further includes an error reminding module, configured to generate error reminding information to remind a user of dispensing errors when the first drug information is inconsistent with the second drug information.
In an embodiment, the error reminding module is further configured to extract difference information of the first medicine information and the second medicine information when the first medicine information is inconsistent with the second medicine information; determining an error category of the dispensing error based on the difference information; and determining the error reminding information corresponding to the error category based on a preset error information list and the error category, and generating the error reminding information.
In an embodiment, the first medicine information and the second medicine information include a medicine type, a medicine name, and a medicine number.
It should be noted that, for convenience and brevity of description, specific working procedures of the above-described apparatus and each module may refer to corresponding procedures in the foregoing embodiment of the drug label identification method, and will not be described herein again.
The apparatus provided by the above embodiments may be implemented in the form of a computer program which may be run on a computer device as shown in fig. 5.
Referring to fig. 5, fig. 5 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device may be a server.
With reference to FIG. 5, the computer device includes a processor, memory, and a network interface connected by a system bus, where the memory may include a non-volatile storage medium and an internal memory.
The non-volatile storage medium may store an operating system and a computer program. The computer program comprises program instructions that, when executed, cause the processor to perform any of a number of drug label identification methods.
The processor is used to provide computing and control capabilities to support the operation of the entire computer device.
The internal memory provides an environment for the execution of a computer program in a non-volatile storage medium that, when executed by a processor, causes the processor to perform any of a number of drug label identification methods.
The network interface is used for network communication such as transmitting assigned tasks and the like. It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
It should be appreciated that the processor may be a central processing unit (Central Processing Unit, CPU), it may also be other general purpose processors, digital signal processors (DIGITAL SIGNAL processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), field-programmable gate array (field-programmable GATEARRAY, FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Wherein in one embodiment the processor is configured to run a computer program stored in the memory to implement the steps of:
acquiring a medicine bottle image and medicine bottle weight information of a target medicine bottle and a medicine image and medicine weight information of a target medicine;
Identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and the medicine bottle weight information;
determining second medicine information of the target medicine based on the medicine image and the medicine weight information;
and when the first medicine information is consistent with the second medicine information, generating a medicine label of the target medicine based on the first medicine information and/or the second medicine information.
In an embodiment, the processor, when implementing the determining the second drug information of the target drug based on the drug image and the drug weight information, is configured to implement:
Identifying the number of the target medicines and appearance information of the target medicines based on the medicine images;
determining a single product weight of the target drug based on the number of target drugs and the drug weight information;
And based on the appearance information of the target medicine and the weight of the single product, comparing and inquiring in a preset medicine information base to obtain the second medicine information.
In an embodiment, the appearance information of the target drug includes an appearance type, shape, and color of the target drug.
In an embodiment, before implementing the comparison query in a preset drug information base based on the appearance information of the target drug and the weight of the single product, the processor is further configured to implement:
Acquiring data in the field of medicine profession;
extracting professional medicine information in the medicine professional field data based on a preset medicine information category;
And constructing the medicine information base based on the professional medicine information.
In an embodiment, after implementing the determining the second drug information of the target drug based on the drug image and the drug weight information, the processor is further configured to implement:
And when the first medicine information is inconsistent with the second medicine information, generating error reminding information so as to remind a user of dispensing errors.
In an embodiment, when the processor generates the error reminding information to remind the user of the dispensing error when the first medicine information is inconsistent with the second medicine information, the processor is configured to:
extracting difference information of the first medicine information and the second medicine information when the first medicine information is inconsistent with the second medicine information;
Determining an error category of the dispensing error based on the difference information;
And determining the error reminding information corresponding to the error category based on a preset error information list and the error category, and generating the error reminding information.
In an embodiment, the first medicine information and the second medicine information include a medicine type, a medicine name, and a medicine number.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, the computer program comprises program instructions, and the processor executes the program instructions to realize any drug label identification method provided by the embodiment of the application.
The computer readable storage medium may be an internal storage unit of the computer device according to the foregoing embodiment, for example, a hard disk or a memory of the computer device. The computer readable storage medium may also be an external storage device of the computer device, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD), or the like, which are provided on the computer device.
While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims (10)

1. A method of identifying a medication label, the method comprising:
acquiring a medicine bottle image and medicine bottle weight information of a target medicine bottle and a medicine image and medicine weight information of a target medicine;
Identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and the medicine bottle weight information;
determining second medicine information of the target medicine based on the medicine image and the medicine weight information;
and when the first medicine information is consistent with the second medicine information, generating a medicine label of the target medicine based on the first medicine information and/or the second medicine information.
2. The medication label identification method of claim 1, wherein the determining second medication information for the target medication based on the medication image and the medication weight information comprises:
Identifying the number of the target medicines and appearance information of the target medicines based on the medicine images;
determining a single product weight of the target drug based on the number of target drugs and the drug weight information;
And based on the appearance information of the target medicine and the weight of the single product, comparing and inquiring in a preset medicine information base to obtain the second medicine information.
3. The drug label identification method of claim 2, wherein the appearance information of the target drug includes an appearance type, a shape, and a color of the target drug.
4. The method for identifying a drug label according to claim 2, wherein the comparing and inquiring are performed in a preset drug information base based on the appearance information of the target drug and the weight of the individual drug, and before the second drug information is obtained, further comprising:
Acquiring data in the field of medicine profession;
extracting professional medicine information in the medicine professional field data based on a preset medicine information category;
And constructing the medicine information base based on the professional medicine information.
5. The drug label identification method according to claim 1, wherein after the second drug information of the target drug is determined based on the drug image and the drug weight information, further comprising:
And when the first medicine information is inconsistent with the second medicine information, generating error reminding information so as to remind a user of dispensing errors.
6. The medication label identification method of claim 5, wherein generating an error alert message to alert a user of a medication dispensing error when the first medication information is inconsistent with the second medication information, comprises:
extracting difference information of the first medicine information and the second medicine information when the first medicine information is inconsistent with the second medicine information;
Determining an error category of the dispensing error based on the difference information;
And determining the error reminding information corresponding to the error category based on a preset error information list and the error category, and generating the error reminding information.
7. The medication label identification method of any of claims 1-6, wherein the first medication information and the second medication information include a medication category, a medication name, and a medication number.
8. A medication label identifying apparatus, characterized in that the medication label identifying apparatus comprises:
The medicine information acquisition module is used for acquiring medicine bottle images and medicine bottle weight information of the target medicine bottle and medicine images and medicine weight information of the target medicine;
A first medicine information identification module for identifying first medicine information of a medicine corresponding to the target medicine bottle based on the medicine bottle image and medicine bottle weight information;
a second medicine information identification module for determining second medicine information of the target medicine based on the medicine image and the medicine weight information;
And the drug label generating module is used for generating a drug label of the target drug based on the first drug information and/or the second drug information when the first drug information is consistent with the second drug information.
9. A computer device comprising a processor, a memory, and a computer program stored on the memory and executable by the processor, wherein the computer program when executed by the processor implements the steps of the drug label identification method of any one of claims 1 to 7.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program, wherein the computer program, when executed by a processor, implements the steps of the drug label identification method according to any of claims 1 to 7.
CN202311664088.2A 2023-12-06 2023-12-06 Drug label identification method, device, computer equipment and storage medium Pending CN117910493A (en)

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